In silico and in vitro assays reveal potential inhibitors against 3CLpro main protease of SARS-CoV-2

Laboratory and physiological aspects of substitute metazoan models for in vivo pharmacotoxicological analysis

New methods are essential to characterize the performance of substitute procedures for detecting therapeutic action(s) of a chemical or key signal of toxicological events. Herein, it was discussed the applications and advantages of using arthropods, worms, and fishes in pharmacological and/or toxicology assessments. First of all, the illusion of similarity covers many differences between humans and mice, remarkably about liver injury and metabolism of xenobiotics. Using invertebrates, especially earthworms (Eisenia fetida), brine shrimps (Artemia salina, Daphnia magna), and insects (Drosophila melanogaster) and vertebrates as small fishes (Oryzias latipes, Pimephales promelas, Danio rerio) has countless advantages, including fewer ethical conflicts, short life cycle, high reproduction rate, simpler to handle, and less complex anatomy. They can be used to find contaminants in organic matters and water and are easier genetically engineered with orthologous-mutated genes to explore specific proteins involved in proliferative and hormonal disturbances, chemotherapy multidrug resistance, and carcinogenicity. As multicellular embryos, larvae, and mature organisms, they can be tested in bigger-sized replication platforms with 24-, 96-, or 384-multiwell plates as cheaper and faster ways to select hit compounds from drug-like libraries to predict acute, subacute or chronic toxicity, pharmacokinetics, and efficacy parameters of pharmaceutical, cosmetic, and personal care products. Meanwhile, sublethal exposures are designed to identify changes in reproduction, body weight, DNA damages, oxidation, and immune defense responses in earthworms and zebrafishes, and swimming behaviors in A. salina and D. rerio. Behavioral parameters also give specificities on sublethal effects that would not be detected in zebrafishes by OECD protocols.

Identification of novel SARS-CoV-2 3CLpro inhibitors by molecular docking, in vitro assays, molecular dynamics simulations and DFT analyses

Introduction

SARS-CoV-2 pandemic has presented a significant threat to global health and the economy, necessitating urgent efforts to develop effective antiviral drugs. The main protease (3CLpro) of SARS-CoV-2 is a critical target for antiviral therapy due to its essential role in viral replication.

Methods

In order to find new structural types of 3CLpro inhibitors to facilitate the solution to the problem of new virus resistance. Six potential pharmacologically bioactive compounds were identified by utilizing structure-based virtual screening and in vitro assays from the Topscience database containing 10 million compounds.

Results and Discussion

Among these, compounds 34 and 36 exhibited potent inhibitory activity with IC50 values of 6.12 ± 0.42 μM and 4.47 ± 0.39 μM, respectively. To elucidate their binding mechanisms with 3CLpro, all-atom molecular dynamics (MD) simulations were conducted. Principal component analysis (PCA), free energy landscapes (FEL) and dynamic cross-correlation maps (DCCM) revealed that the binding of compounds 34 and 36 to 3CLpro significantly enhanced the structural stability of 3CLpro, reducing conformational flexibility and internal motions. The results of protein-ligand interaction showed that compounds 34 and 36 formed strong and stable interactions to key residues at active site of 3CLpro with different binding modes from S-217622. And HOMO-LUMO gap and molecular electrostatic potential distribution revealed the quantum chemical properties of compounds 34 and 36. These findings suggested that compounds 34 and 36 can be as novel SARS-CoV-2 3CLpro inhibitors and promising lead-like drug candidates for developing COVID-19 treatments.

Comprehensive In silico analysis of chaperones identifies CRYAB and P4HA2 as potential therapeutic targets and their small-molecule inhibitors for the treatment of cholangiocarcinoma

Cholangiocarcinoma (CCA) is a subtype of liver cancer with increasing incidence, poor prognosis, and limited treatment modalities. It is, therefore, imperative to identify novel therapeutic targets for better management of the disease. Chaperones are known to be significant regulators of carcinogenesis, however, their role in CCA remains unclear. This study aims to screen chaperones involved in CCA pathogenesis and identify drugs targeting key chaperones to improve the therapeutic response to the disease. To achieve this, first we mined the literature to create an atlas of human chaperone proteins. Next, their expression in CCA was determined by publicly available datasets of patients at mRNA and protein levels. In addition, our analysis involving protein-protein interaction and pathway analysis of eight key dysregulated chaperones revealed that they control crucial cancer-related pathways. Furthermore, topology analysis of the CCA network identified crystallin alpha-B protein (CRYAB) and prolyl-4-hydroxylase subunit 2 (P4HA2) as novel therapeutic targets for the disease. Finally, drug repurposing of 286 clinically approved anti-cancer drugs against these two chaperones performed by molecular docking and molecular dynamics simulations showed that tucatinib and regorafenib had a modulatory effect on them and could be potential inhibitors of CRYAB and P4HA2, respectively. Overall, our study, for the first time, provides insights into the pan-chaperone expression in CCA and explains the pathways that might drive CCA pathogenesis. Further, our identification of potential therapeutic targets and their inhibitors could provide new and complementary approaches to CCA treatment.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.